GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers

Publication Overview
TitleGWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers
AuthorsLiu R, Gong J, Xiao X, Zhang Z, Li J, Liu A, Lu Q, Shang H, Shi Y, Ge Q, Iqbal MS, Deng X, Li S, Pan J, Duan L, Zhang Q, Jiang X, Zou X, Hafeez A, Chen Q, Geng H, Gong W, Yuan Y
TypeJournal Article
Journal NameFrontiers in plant science
Volume9
Year2018
Page(s)1067
CitationLiu R, Gong J, Xiao X, Zhang Z, Li J, Liu A, Lu Q, Shang H, Shi Y, Ge Q, Iqbal MS, Deng X, Li S, Pan J, Duan L, Zhang Q, Jiang X, Zou X, Hafeez A, Chen Q, Geng H, Gong W, Yuan Y. GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers. Frontiers in plant science. 2018; 9:1067.

Abstract

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.
Germplasm
This publication contains information about 2 stocks:
Stock NameGRIN IDSpeciesType
LMY28 x XLZ24, RILGossypium hirsutumpopulation
AD1_LX-RIL_231Gossypium hirsutumpanel
Features
This publication contains information about 1,031 features:
Feature NameUniquenameType
NAU_TM20105_chr07_32806008NAU_TM20105_chr07_32806008genetic_marker
NAU_TM35248_chr10_61465113NAU_TM35248_chr10_61465113genetic_marker
NAU_TM42589_chr12_74294300NAU_TM42589_chr12_74294300genetic_marker
NAU_TM47737_chr13_79840646NAU_TM47737_chr13_79840646genetic_marker
NAU_TM50928_chr14_12292322NAU_TM50928_chr14_12292322genetic_marker
NAU_TM53695_chr17_7193789NAU_TM53695_chr17_7193789genetic_marker
NAU_TM54872_chr17_34920546NAU_TM54872_chr17_34920546genetic_marker
NAU_TM54867_chr17_34643835NAU_TM54867_chr17_34643835genetic_marker
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NAU_TM57274_chr19_13727112NAU_TM57274_chr19_13727112genetic_marker
NAU_TM57779_chr19_27578455NAU_TM57779_chr19_27578455genetic_marker
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NAU_TM74739_chr20_53230049NAU_TM74739_chr20_53230049genetic_marker
NAU_TM55476_chr22_2630904NAU_TM55476_chr22_2630904genetic_marker
NAU_TM55461_chr22_2087134NAU_TM55461_chr22_2087134genetic_marker
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NAU_TM67343_chr24_7799808NAU_TM67343_chr24_7799808genetic_marker
NAU_TM68035_chr24_18455652NAU_TM68035_chr24_18455652genetic_marker

Pages

Projects
This publication contains information about 2 projects:
Project NameDescription
LX-RIL-2018
AD1-NBI_fiber-yield_CRI-Yuan-2018_GWAS
Featuremaps
This publication contains information about 1 maps:
Map Name
LMY28 x XLZ24, RIL (2018)
Properties
Additional details for this publication include:
Property NameValue
DOI10.3389/fpls.2018.01067
Elocation10.3389/fpls.2018.01067
ISSN1664-462X
Journal AbbreviationFront Plant Sci
Journal CountrySwitzerland
LanguageEnglish
Language Abbreng
pISSN1664-462X
Publication Date2018
Publication ModelElectronic-eCollection
Publication TypeJournal Article
Published Location1067